White Paper

Harnessing Cost-to-Serve Optimization

CTSO is a complex optimization that evaluates billions of alternatives and configuration changes that lead to better decision-making through quantification.

Activity-based costing is a snapshot of the true cost of business process or set of processes anywhere in the business. Cost-to-serve is the true total end-to-end cost of each individual product-customer combination.

CTSA tells you where you are—what it costs to serve a customer with a product at a service level. CTSO tells you what to do—what it should cost and how to optimize the network to acheive that cost.

Harnessing Cost-to-Serve Optimization

For Increased Customer and Product Profitability

What is the real cost to meet this customer’s needs?
How much will it cost to increase service levels from 90 percent to 95 percent?

The inability to answer questions like these means you are likely making uninformed business decisions and even unknowingly servicing unprofitable customers. How much time and resources are being wasted as a result?

The ultimate goal is to increase company profitability by making unprofitable customers profitable or helping profitable customers become even more profitable. Without accurate cost-to-serve data for current customers and products, this is a near-impossible task. An accurate cost-to-serve model enables informed decision making by answering questions such as:

Is this customer or customer segment profitable, given the supply chain configuration and costs?

Does it make good business sense to continue to stock and distribute this product?

What is the right amount to charge to at least cover my costs?

With an accurate cost-to-serve and margin-to-serve model (when sale price data is incorporated), better business decisions can be made and financial supply chain optimization is possible.

What Can Be Learned From This White Paper?

The key principles of cost-to-serve optimization and how it differs from cost-to-serve analysis and activity-based costing

The alternatives that cost-to-serve optimization present along with the potential benefits and impacts of implementation

What Is Cost-to-Serve Optimization?

Cost-to-serve is the analysis and quantification of all activities and related costs incurred in order to fulfill customer demand for a product through the end-to-end supply chain. Accurate cost-to-serve metrics are developed by modeling supply chain activities within the network while accumulating and properly allocating fixed and variable costs. There are multiple methods and disciplines to achieve true cost-to-serve, and the distinctions between them are not always clear. The terms “activity-based costing” (ABC) and “cost-to-serve analysis” (CTSA) are two modeling approaches, both of which require allocation of indirect costs to cost drivers within a process or supply chain model. Supply chain network design and cost-to-serve optimization are both supply chain optimization disciplines that can identify opportunities to reduce costs and increase profitability.

Identifying the Right Supply Chain Costing Method

A starting point for understanding the two different methods is first recognizing that while activity-based costing is not cost-to-serve. they do utilize a similar approach. Both methods focus on allocating indirect cost pools-overhead or fixed costs that are not easily and directly attributable to a single order, shipment, or activity-to individual products or product groups. Both also seek to make clear the “invisible” costs in the process or network being examined. However, the use, context and level of detail of the two methods are different.

Activity-based costing (ABC) is often used by the finance department to
cost out and predict the budget of departments, processes, or business activities under changing loads of cost drivers. Without an ABC model, the financial impact of product mix and volume changes can be misunderstood, which can lead to poor decision making. ABC helps finance focus on total product costs within the four walls of the organization and identifies all of the relevant activities in a process or organization of interest. It can also identify natural cost drivers such as labor hours or product quantity, which can be related to an indirect cost pool. By making a detailed model of all the value and non-value added activities performed in the process. and connecting the activity drivers more directly to all of the relevant cost pools, the resulting cost model is much more precise than other more traditional methods for determining “what-if” budgets. ABC models are very detailed, time-intensive to prepare. and are typically used to supplement traditional cost accounting methods to analyze specific financial decisions. ABC is not typically applied to an end sales item at the point of transfer to the customer.

Cost-to-serve (CTS) crosses all functional areas in the supply chain and is
intended to accurately assess the total profitability of an individual product or item being sold to a customer. CTS models incorporate all activities necessary to complete the customer delivery and collect product revenue. It captures how each major supply chain activity affects the complete end-to-end cost-to-serve each customer or total landed cost for a product. Stated differently, it is the determination of the total cost of servicing each individual customer at an SKU level and at the designated level of service.

An analyst conducting a CTS project must identify where costs occur in the supply chain. CTS recognizes that each product and customer combination is different, and therefore will have different costs. This analysis is most meaningful when looking at trends-product categories and customer types (individual product/customer combination analysis may be too granular). When price is added to the equation, it also calculates customer account profitability.

Although it is tempting to use cost-to-serve as a tool for making changes to the business, this strategy can be very dangerous and misleading. Dropping customers and/or products that are identified as unprofitable in a CTS model also drops the associated revenue, without guaranteeing that the associated fixed costs will be shed. CTS analysis is best thought of as a way for management to understand the relative profitability of various customer or product segments of the business. To actually use CTS as a decision making tool, it is necessary to link changes in the network model to both revenue and fixed costs. A CTS model with fixed cost and revenue relationships in place can enable an accurate prediction of the CTS of a future state. Finding a better configuration using CTS modeling is called cost-to-serve optimization (CTSO).

The technology and modeling approach needed to effectively perform cost-to-serve optimization is very similar to those used in supply chain network design (SCND). SCND also enables evaluation and optimization of the entire end-to-end supply chain from a financial basis. Network structure, supply chain policies, and integrated operations are evaluated to optimize the trade-offs of cost, time and capacity in the network. SCND realigns the manufacturing footprint and distribution structure, incorporating inventory and transportation costs in order to achieve a system-wide “global” optimization.

Finding a better configuration using CTS modeling is called cost-to-serve optimization (CTSO).

While CTSO and SCND use the same modeling technology, the objectives and the necessary level of model detail is different and CTSO utilizes more detailed financials. CTSO incorporates the decisions around whether or not to serve various customers and whether or not to deliver various products, in order to avoid incurring fixed costs (labor, shifts, assets/capacity, facility charges). Indirect and direct cost pools are allocated as part of the model to ensure that each alternative configuration is as accurate as possible. CTSO is usually performed with individual SKUs and customers. In contrast, SCND typically relies on product aggregation and often customer-demand aggregation as well.

Supply chain network design focuses on optimizing network structure based on capacity constraints and aggregate overall flows of materials through the network. Cost-to-serve optimization optimizes the network by preserving visibility into the profitability of individual customers and products and finds a configuration that drops fixed costs at greater rate than it drops margin.

Differentiating cost-to-serve analysis from cost-to-serve optimization is simple-analysis only models the current state and identifies issues. It accounts for the total cost of serving customers and the total delivered cost of each product by customer. CTSO provides information with which to make decisions, as it actually optimizes the result. It evaluates the thousands of ABC options to identify the optimal network design, structure and flow to achieve the lowest total CTS based on all end-to-end trade-offs.

What does Cost-to-Serve Optimization Provide?

Wouldn’t you want to know if:

20 percent or more of customer orders make negative profit margins?

10 percent or more of customers are unprofitable?

5-10 percent of of the product portfolio makes no contribution?

Recognizing that different customers, products, service levels and distribution channels each contribute different margins, first identify the unprofitable and low-margin product and customer combinations and high-cost processes, then develop action plans for each in order to improbe the business’ profitability.

A small investment in cost-to-serve analysis can pay off immediatly by identifying key issues that become the basis for a plan of action. The graphic below is an example of CTSA taken from an actual client’s line-of-business.

This analysis yielded an extremely high percentage of customers (nearly 44 percent) that were either unprofitable or contributed no margin. By executing a CTSA, this client identifies significant immediate action items for improving profitability. Perhaps more importantly, they gained intelligence with which to foster long-term improvements.

Obviously, further analysis was necessary to determine the causes for this issue and the courses of action can vary.

With these data in hand, the client was able to perform a cost-to-serve optimization, then make strategic decisions about which actions to take to improve margins for unprofitable customers (increase prices/reduce service), and how to improve high-cost processes to increase profitability.

When a client conducted an analysis on thier product and source point portfolio, it resulted in 41 SKUs being discontinues at specific source points due to excessive costs. (see graphic below)

Note that the objective is not to eliminate customers nor to abandon products, but rather to make every customer and product combination as profitable as possible. Further, implementing changes must be done carefully so as not to remove unprofitable customers and/ or products and leave fixed costs in place, (which become an allocated burden and reduce profitability for other customers and products).

CTSO is a compled optimization that evaluates billions of alternatives and configuration changes that lead to better decision-making through quantification. It identifies characteristics of customers and of products that increase costs, isolates high-cost prosesses and recommends alternatives to mitigate those costs.

Because CTSO is a fragile analysis, where changing one element may result in significant impacts on other ares, simulation is particularly relevant and can be employed to depict the solutions’ effect over time. Detailed simulation of a cost-to-serve analysis can also be performed to determine precise costing of defined alternatives of interest to the CFO.

Conclusion

Historically, becuase of their complexity and labor-intensive nature, activity-based costing or cost-to-serve analysis initiatives were performed only every one to three years to help a company realign its product and customer service profiles and minimize process costs. Now, cost-to-serve optimization projects can be accomplished in weeks or less. Models can be run at the SKU level within customer, with multiple time periods, and entire end-to-end supply chains can be evaluated and optimized quickly, making this type of analysis possible as an ongoing activity.

LLamasoft Is Here to Help

LLamasoft is dedicated to helping businesses build optimized supply chains that help them thrive even in changing market conditions. Partnering with LLamasoft ensures you’ll have more than just software and technical support, but a growing community of supply chain design practitioners, workshops, training and coaching to guide you as you progress. To learn more, email info@llamasoft.com or call 866-598-9831.

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